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FER2013 dataset #5120

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merged 5 commits into from
Jan 5, 2022
Merged

FER2013 dataset #5120

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57ea2d6
add prototype dataset
pmeier Dec 21, 2021
e647f45
add old style dataset
pmeier Dec 21, 2021
41df18e
Apply suggestions from code review
pmeier Jan 5, 2022
68982c6
refactor integrity check
pmeier Jan 5, 2022
7d70aab
Merge branch 'main' into datasets/fer2013
pmeier Jan 5, 2022
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refactor integrity check
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@pmeier
pmeier committed Jan 5, 2022
commit 68982c6ae14a06f939b788954faf0c1999bccccc
27 changes: 12 additions & 15 deletions torchvision/datasets/fer2013.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
import csv
import os
import os.path
import pathlib
from typing import Any, Callable, Optional, Tuple

import torch
Expand Down Expand Up @@ -38,7 +37,17 @@ def __init__(
self._split = verify_str_arg(split, "split", self._RESOURCES.keys())
super().__init__(root, transform=transform, target_transform=target_transform)

with open(self._verify_integrity(), "r", newline="") as file:
base_folder = pathlib.Path(self.root) / "fer2013"
file_name, md5 = self._RESOURCES[self._split]
data_file = base_folder / file_name
if not check_integrity(str(data_file), md5=md5):
raise RuntimeError(
f"{file_name} not found in {base_folder} or corrupted. "
f"You can download it from "
f"https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge"
)

with open(data_file, "r", newline="") as file:
self._samples = [
(
torch.tensor([int(idx) for idx in row["pixels"].split()], dtype=torch.uint8).reshape(48, 48),
Expand All @@ -62,17 +71,5 @@ def __getitem__(self, idx: int) -> Tuple[Any, Any]:

return image, target

def _verify_integrity(self):
base_folder = os.path.join(self.root, "fer2013")
file_name, md5 = self._RESOURCES[self._split]
file = os.path.join(base_folder, file_name)
if not check_integrity(file, md5=md5):
raise RuntimeError(
f"{file_name} not found in {base_folder} or corrupted. "
f"You can download it from "
f"https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge"
)
return file

def extra_repr(self) -> str:
return f"split={self._split}"